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Multi-omics Boot Camp at Columbia University 2025

Many observational studies are now leveraging modern technologies to measure multiple types of omic data. Omic tools can assist in better characterizing risk factors (e.g. germline genetics, exposomics), providing measurements for intermediate variables that may capture the underlying mechanism (e.g. transcriptomics, proteomics, metabolomics, and the microbiome), or defining an outcome of interest. In this context, the investigator is often confronted with an analytic decision on a continuum between simplicity and complexity. Simple approaches often treat sets of variables in a pairwise independent manner, sacrificing joint evaluation for benefits in interpretability. At the other extreme, complex methods may more-completely model the joint omics structure, but can sacrifice interpretability. This workshop will cover several different approaches to the analysis of multiple omic data, with a focus on the tradeoffs between simple and complex approaches.

This three-day intensive workshop will provide an overview of multiple approaches to analyze multiple omic data types measured on the same individuals or via the use of summary statistic data. Instructors have experience in developing and applying methods for omic analysis in genetic and environmental epidemiology and are members of an active program project focused on developing statistical methods for integrated analysis. The workshop will include seminar lectures with hands-on computer lab sessions to put concepts into practice. Since the analysis of multi-omic data is broad in scope, the workshop will survey a range of approaches and highlight the appropriate application and interpretation of each approach for specific research questions. The lab sessions will provide an opportunity to work hands-on with different types of omic data.

Table of Content

Summary

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Benefits

By the end of the workshop, participants will be familiar with the following topics:

  • Data reduction, including clustering.
  • Regression analysis, including regularized regression, hierarchical models, and partial least squares.
  • Interaction analysis and Genome-wide interaction scans (GWIS).
  • Mediation analysis.
  • Polygenic/polyexposure analysis.
  • Integrative analysis using genome-wide association study (GWAS) summary statistics.

Requirements

Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this training:

  1. Each participant must have an introductory background in statistics and epidemiology.
  2. Each participant must be familiar with R.
  3. Each participant is required to have a personal laptop/computer and a free, basic RStudio Cloud account. All lab sessions will be done using RStudio Cloud.

Interview Dates and Process

Summer 2025: The Multi-omics Boot Camp is a livestream, remote training that takes place over live, online video. With the instructors on the west coast, the Boot Camp will take place on May 28-30, 2025 from 12pm - ~6:15pm EDT (9am - ~3:15pm PDT). Please note this training is not a self-paced, pre-recorded online training.

Application Deadline

May 30, 2025

How To Apply

For more details visit Columbia University Training Webpage

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